Document Detail


Using multidimensional projection techniques for reaching a high distinguishing ability in biosensing.
MedLine Citation:
PMID:  21437775     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Recent advances in the control of molecular engineering architectures have allowed unprecedented ability of molecular recognition in biosensing, with a promising impact for clinical diagnosis and environment control. The availability of large amounts of data from electrical, optical, or electrochemical measurements requires, however, sophisticated data treatment in order to optimize sensing performance. In this study, we show how an information visualization system based on projections, referred to as Projection Explorer (PEx), can be used to achieve high performance for biosensors made with nanostructured films containing immobilized antigens. As a proof of concept, various visualizations were obtained with impedance spectroscopy data from an array of sensors whose electrical response could be specific toward a given antibody (analyte) owing to molecular recognition processes. In addition to discussing the distinct methods for projection and normalization of the data, we demonstrate that an excellent distinction can be made between real samples tested positive for Chagas disease and Leishmaniasis, which could not be achieved with conventional statistical methods. Such high performance probably arose from the possibility of treating the data in the whole frequency range. Through a systematic analysis, it was inferred that Sammon's mapping with standardization to normalize the data gives the best results, where distinction could be made of blood serum samples containing 10(-7) mg/mL of the antibody. The method inherent in PEx and the procedures for analyzing the impedance data are entirely generic and can be extended to optimize any type of sensor or biosensor.
Authors:
Fernando V Paulovich; Rafael M Maki; Maria C F de Oliveira; Marcelle C Colhone; Fabiana R Santos; Vanessa Migliaccio; Pietro Ciancaglini; Katia R Perez; Rodrigo G Stabeli; Angelo C Perinoto; Osvaldo N Oliveira; Valtencir Zucolotto
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-3-25
Journal Detail:
Title:  Analytical and bioanalytical chemistry     Volume:  -     ISSN:  1618-2650     ISO Abbreviation:  -     Publication Date:  2011 Mar 
Date Detail:
Created Date:  2011-3-25     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101134327     Medline TA:  Anal Bioanal Chem     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Instituto de Ciências Matemáticas e de Computação, USP, CP 668, São Carlos, 13560-970, São Paulo, Brazil.
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